sDeepFM: Multi-Scale Stacking Feature Interactions for Click-Through Rate Prediction
نویسندگان
چکیده
منابع مشابه
Ensemble of Collaborative Filtering and Feature Engineered Models for Click Through Rate Prediction
The challenge for Track 2 of the KDD Cup 2012 competition was to predict the click-through rate (CTR) of web advertisements given information about the ad, the query and the user. Our solution comprised an ensemble of models, combined using an artificial neural network. We built collaborative filters, probability models, and feature engineered models to predict CTRs. In addition, we developed a...
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To better extract users’ interest by exploiting the rich historical behavior data is crucial for building the click-through rate (CTR) prediction model in the online advertising system in e-commerce industry. There are two key observations on user behavior data: i) diversity. Users are interested in different kinds of goods when visiting e-commerce site. ii) local activation. Whether users clic...
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ژورنال
عنوان ژورنال: Electronics
سال: 2020
ISSN: 2079-9292
DOI: 10.3390/electronics9020350